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Edera Protect AI
Hardware-isolated containers, at native speed.
About Edera Protect AI
Edera Protect AI is a hardened runtime solution that provides hardware-based isolation for Kubernetes workloads, including AI agents and GPU-bound applications. It addresses the security risks of shared kernels by giving each Kubernetes pod its own microVM, with its own Linux kernel, creating a hardware boundary that prevents lateral movement and contains potential breaches. The platform is designed to be a drop-in replacement for standard Kubernetes runtimes, requiring no changes to the control plane, nodes, operating system, or container images. It supports mainstream Linux distributions and works on any cloud or on-premises environment. Edera boasts performance within 5% of native, ensuring minimal impact on workload efficiency. Key features include per-zone kernel customization for GPU nodes, full native observability with kubectl top and horizontal pod autoscaling, and the ability to run untrusted, AI-generated, or third-party code without needing to trust the code itself. Edera aims to simplify secure infrastructure, enabling organizations to adopt multi-tenancy and AI agents with confidence, while reducing costs by eliminating the need for dedicated single-tenant resources.
Challenges It Solves
- Containers share the host kernel, making them vulnerable to kernel exploits that can affect all tenants.
- AI agents and untrusted code require isolation but often do not perform well with traditional VMs or sandboxes.
- Secure multi-tenancy in Kubernetes is difficult without hardware-level boundaries.
- GPU workloads require isolation to prevent cross-tenant data exposure, but current solutions have significant performance overhead.
Screenshots
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Use Cases
Multi-Tenancy for Kubernetes
Edera provides hardware boundaries between tenants on shared Kubernetes clusters, ensuring that one tenant cannot compromise another.
Multi-Tenancy for GPUs
Edera enables GPU sharing among multiple tenants with zero blast radius, preventing GPU-related attacks and data leaks.
AI Agent Execution
AI agents can run freely in production inside a hardware-isolated boundary that they cannot cross, allowing organizations to deploy autonomous agents securely.
Untrusted Execution
Run code that you don't trust—such as AI-generated code, third-party code, or open-source libraries—without worrying about security risks.
Trust & Compliance
Every workload runs in a verifiable, isolated zone, providing an auditable trail that proves compliance.
Observability & Tuning
See exactly what every workload is doing in real-time and tune performance and resource usage with confidence.
Pricing
Custom pricing — built for your team
Edera Protect AI pricing is tailored to your organisation's size, integrations, and requirements. AiDOOS generates your proposal instantly — scoped & ready in seconds.
Key Features
Each Kubernetes pod runs in its own microVM with a dedicated Linux kernel, giving true hardware isolation.
Workloads run within 5% of native performance, ensuring no significant performance penalty.
Runs on any Kubernetes distribution including EKS with no changes to control plane, node, OS, or images.
Deploy on any instance in any public cloud or on-premises environment.
Pin a different kernel and driver version per zone on shared GPU nodes, enabling GPU multi-tenancy with zero blast radius.
kubectl top, horizontal pod autoscaling, and existing metrics work seamlessly.
What Reviewers Say
What works well
- Provides true hardware isolation for containers, eliminating the shared kernel risk.
- Near-native performance with minimal overhead (within 5%).
- Drop-in compatibility with existing Kubernetes environments, requiring no changes.
- Enables secure multi-tenancy for GPUs, allowing shared GPU infrastructure without cross-tenant risk.
Common concerns
- Requires understanding of microVM concepts and runtimeclass configuration.
- May have higher overhead than standard container runtimes due to hardware virtualization.
- Early access stage; comprehensive documentation and support may be limited.
Reviews
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Enterprise Readiness
Identity & Access
Data Security
SLA & Availability
Compliance & Portability
Integrations
Kubernetes
Edera Hardened Runtime integrates with Kubernetes as a drop-in runtime via RuntimeClass, providing hardware isolation for pods.
Amazon EKS
Edera supports Amazon EKS for running isolated workloads on AWS with no node or control-plane changes.
Generic Kubernetes
Runs on any Kubernetes cluster via RuntimeClass, enabling hardware isolation for untrusted workloads.
NVIDIA GPUs
Edera provides per-zone kernels for GPUs, allowing pinning of different kernel and driver versions on shared GPU nodes.
Linux
Edera runs on Linux distributions including Amazon Linux and Ubuntu, supporting various kernels and drivers.
GitHub
Edera's code is open-source on GitHub, allowing community collaboration and visibility into the runtime.
Prometheus
Edera provides full native observability, working with existing metrics and monitoring tools like Prometheus.
Governance & Compliance
EU AI Act
No data available
Data Processing Agreement
No data available
Sub-processors
No data available
Right to Erasure
No data available
Change Notifications
No data available
NIST AI RMF
No data available
AiDOOS Managed Deployment
Deploy Edera Protect AI in 72 hours
AiDOOS handles setup, CRM integration, SSO config, and user provisioning. Your team goes live — not your IT department.
Prerequisites
- Kubernetes cluster
- Linux-based nodes
- Root access to nodes
Configuration Options
- RuntimeClass configuration
- GPU zone setup
- Monitoring integration
How Edera Protect AI Compares
| Product | AI & Analytics | Ease of Use | Enterprise Features | Pricing | Integrations | Mobile Experience | Quick Setup | Customer Support | Rating | Price/mo |
|---|---|---|---|---|---|---|---|---|---|---|
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Edera Protect AI This product
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Good | Good | Excellent | Good | Good | Poor | Good | Good | — | $Custom/user |
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DO
Docker
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Good | Excellent | Good | Good | Excellent | Poor | Excellent | Good | — | $Custom/user |
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KC
Kata Containers
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Good | Good | Good | Good | Good | Poor | Good | Fair | — | $Custom/user |
|
FC
Firecracker
|
Good | Good | Good | Good | Good | Poor | Good | Fair | — | $Custom/user |
A Virtual Delivery Center for Edera Protect AI
Pre-vetted experts and AI agents in the loop, assembled as a delivery pod. Pay in Delivery Units — universal pricing across roles, seniority, and tech stacks. No hiring, no contracting, no procurement cycle.
- Plans from $2,000 — Starter Pack, 10 Delivery Units, 90 days
- Refundable on unused Delivery Units, anytime — no questions asked
- Re-delivery guarantee on acceptance miss
- Pre-flight delivery sizing — you see the plan before you commit
How a Virtual Delivery Center delivers Edera Protect AI
Outcome-based delivery via AiDOOS’s VDC model. Why VDC vs traditional consulting? →
Outcome-Based
Pay for results, not hours
Milestone-Driven
Clear deliverables at each phase
Expert Network
Access to certified specialists